Update app.py

app.py

@@ -53,7 +53,7 @@ def dice_coef(y_true, y_pred, smooth=1):
 seg_model = tf.keras.models.load_model('seg_unet_model.h5', custom_objects={'Combo_loss': Combo_loss, 'dice_coef': dice_coef})
 
 inputs = gr.inputs.Image(type="pil", label="Upload an image", source="upload")
-image_output = gr.outputs.Image(type="numpy", label="Output Image")
+image_output = gr.outputs.Image(type="pil", label="Output Image")
 # outputs = gr.outputs.HTML() #uncomment for single class output 
 
 
@@ -73,9 +73,6 @@ def gen_pred(img=inputs, model=seg_model):
     img_bytes = pred.tobytes()
     nparr = np.frombuffer(img_bytes, np.byte)
     pred_pil = cv2.imdecode(nparr, cv2.IMREAD_REDUCED_COLOR_8)
-    # color_coverted = cv2.cvtColor(pred, cv2.COLOR_BGR2RGB)
-    # pil_image = Image.fromarray(pred)
-    # PIL_image = Image.fromarray(pred.astype('uint8'), 'RGB')
     # return "UI in developing process ..."
     return pred_pil
 
@@ -85,7 +82,7 @@ description = "Upload an image and get prediction mask"
 
 gr.Interface(fn=gen_pred, 
              inputs=inputs, 
-             outputs="image", 
+             outputs=image_output, 
              title=title, 
              examples=[["003e2c95d.jpg"], ["003b50a15.jpg"], ["003b48a9e.jpg"], ["0038cbe45.jpg"], ["00371aa92.jpg"]],
              # css=css_code,